# MK Sistem Kendali Cerdas

## Identitas

* Kode : TKE194941 Sistem Kendali Cerdas
* SKS : 3 SKS
* Jadwal:
  * Kelas A : Ruang E-201, Jum'at 13.55, 3 mhs
* Metode: Case-based dan Project-based Learning
* Semester Mata Kuliah: 6
* Sifat Mata Kuliah: Teknik Elektro Pendalaman (TED)

### Materi

1. Pendahuluan
2. Dasar-dasar Logika Fuzzy
3. Sistem Inferensi Fuzzy
4. Sistem Inferensi Fuzzy untuk Sistem Kendali
5. Proyek Sistem Inferensi Fuzzy untuk Sistem Kendali
6. Proyek Sistem Inferensi Fuzzy untuk Sistem Kendali
7. Pendahuluan Neural Network
8. Neural Network dalam Sistem Kendali
9. Neural Network dalam Sistem Kendali
10. Neural Network dalam Sistem Kendali
11. Sistem Neuro-Fuzzy
12. Sistem Neuro-Fuzzy untuk Sistem Kendali
13. Proyek Sistem Neuro-Fuzzy untuk Sistem Kendali
14. Proyek Sistem Neuro-Fuzzy untuk Sistem Kendali

### Referensi Utama

* Liu Jinkun, Intelligent Control Design and MATLAB Simulation \[[website](https://www.springer.com/gp/book/9789811052620#reviews)] \[[m-file download](https://shi.buaa.edu.cn/liujinkun/zh_CN/jxzy/8049/content/1217.htm#jxzy)]
* [Fuzzy and Neural Control by Babuska](https://www.matlabi.ir/wp-content/uploads/bank_papers/c%20paper/c25_www.Matlabi.ir_Fuzzy%20and%20Neural%20Control,%20Robert%20Babuska,%20Lecture%20Notes,%20Delft%20University%20of%20Technology.pdf)
* [Intelligent Control - A Hybrid Approach Based on Fuzzy Logic, Neural Networks and Genetic Algorithms - Nazmul Siddique - Springer](https://www.springer.com/gp/book/9783319021348)
* Himanshu Singh & Yunis Ahmad Lone, Deep Neuro-Fuzzy Systems With Python: With Case Studies and Applications From the Industry \[[website](https://www.apress.com/gp/book/9781484253601)]\[[python download](https://github.com/Apress/deep-neuro-fuzzy-systems-w-python)]
* Hung T. Nguyen & Nadipuram R. Prasad & Carol L. Walker & Elbert A. Walker, A First Course in Fuzzy and Neural Control \[[website](https://www.crcpress.com/A-First-Course-in-Fuzzy-and-Neural-Control/Nguyen-Prasad-Walker-Walker/p/book/9781584882442)]

### Referensi Tambahan

* Roland S Burns, Advanced Control Engineering (Chapter 10) \[[website](https://www.sciencedirect.com/book/9780750651004/advanced-control-engineering#book-description)]
* Ali Zilouchian & Mo Jamshidi, Intelligent Control Systems Using Soft Computing Methodologies, \[[website](https://www.crcpress.com/Intelligent-Control-Systems-Using-Soft-Computing-Methodologies/Zilouchian-Jamshidi/p/book/9780849318757)]\[[ebook download](https://www.wacong.org/freepublicationsbymojamshidi/)]
* Adrian A. Hopgood, Intelligent Systems for Engineers and Scientists, [websites](https://www.routledge.com/Intelligent-Systems-for-Engineers-and-Scientists/Hopgood/p/book/9781138374287)
* Adedeji Bodunde Badiru, Fuzzy Engineering Expert Systems With Neural Network Applications
* Ahmad M. Ibrahim, Fuzzy Logic for Embedded Systems Applications \[[website](https://www.sciencedirect.com/book/9780750676052/fuzzy-logic-for-embedded-systems-applications)]
* Erdal Kayacan & Mojtaba Ahmadieh, Fuzzy Neural Networks for Real Time Control Applications: Concepts, Modeling and Algorithms for Fast Learning \[[website](https://www.elsevier.com/books/fuzzy-neural-networks-for-real-time-control-applications/kayacan/978-0-12-802687-8)]
* James M. Keller & Derong Liu & David B Fogel, Fundamentals of Computational Intelligence: Neural Networks, Fuzzy Systems, and Evolutionary Computation \[[website](https://onlinelibrary.wiley.com/doi/book/10.1002/9781119214403)]
* Steven L Brunton & J Nathan Kutz, Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control \[[website](https://databookuw.com/)]\[[ebook download](https://databookuw.com/databook.pdf)]\[MATLAB [Code](https://databookuw.com/CODE.zip)and [Data](https://databookuw.com/DATA.zip)]\[Python [Code](https://databookuw.com/CODE_PYTHON.zip)and [Data](https://databookuw.com/DATA_PYTHON.zip)]
* [Intelligent Control: Fuzzy Logic Applications - 1st Edition - Clarence](https://www.routledge.com/Intelligent-Control-Fuzzy-Logic-Applications/Silva/p/book/9780849379826)
* [Fuzzy Logic in Control - René Jager - Google Books](https://books.google.co.id/books/about/Fuzzy_Logic_in_Control.html?id=1E0owYZ-ht0C\&redir_esc=y)

### Software Links

* [GNU Octave](https://www.gnu.org/software/octave/)
* [Octave Online](https://octave-online.net/)
* [MATLAB and Simulink](https://www.mathworks.com/products/matlab.html)
* [Anaconda](https://www.anaconda.com/)
* [Google Colab](https://colab.research.google.com/)
* [Fuzzylite](https://fuzzylite.com/) : The FuzzyLite Libraries for Fuzzy Logic Control

### Video Links

* [Neural Network - Online Course - MATLAB Helper - YouTube](https://www.youtube.com/playlist?list=PLmyWlxlLCcz8ct8rKtIO0ESXgEDvh7f5N)
* [Artificial Intelligence Tutorial - YouTube](https://www.youtube.com/playlist?list=PLkmvobsnE0GEeD8ICPS5iwz0GCNhyqSre)
* [Data-Driven Control with Machine Learning - YouTube](https://www.youtube.com/playlist?list=PLMrJAkhIeNNQkv98vuPjO2X2qJO_UPeWR)

### E-learning Link

* [E-learning Sistem Kendali Cerdas 201920202–A](https://eldiru.unsoed.ac.id/course/view.php?id=62)
* [Github Classroom](https://classroom.github.com/classrooms/61479455-sistem-kendali-cerdas-classroom-1)

## Neuro-fuzzy in Python

### Libraries

* numpy `conda install -c conda-forge numpy`, `pip install numpy`
* scipy `conda install -c conda-forge scipy`, `pip install scipy`
* scikit fuzzy `conda install -c conda-forge scikit-fuzzy`, `pip install scikit-fuzzy`
* scikit learn `conda install -c conda-forge scikit-learn`, `pip install scikit-learn`
* fuzzylite `pip install pyfuzzylite`
* pandas `conda install -c conda-forge pandas`, `pip install pandas`
* statsmodels `conda install -c conda-forge statsmodels`,`pip install statsmodels`
* keras `conda install -c conda-forge keras`, `pip install keras`
* anfis `pip install anfis`
* bokeh `conda install -c conda-forge bokeh`, `pip install bokeh`
* fuzzycmeans `pip install fuzzycmeans`

### Downgrade Python for installing keras and tensorflow

* `python --version`
* `conda search python` : check installed version of python
* `conda install python=3.6.0`: downgrade to your preferred python